Evidence map›Paper›PMID 28263465›Full record

ReviewClinical pharmacology in drug development2017

Pharmacokinetic Considerations for Combining Antiretroviral Therapy, Direct-Acting Antiviral Agents for Hepatitis C Virus, and Addiction Treatment Medications.

Cindy J Bednasz, Charles S Venuto, Qing Ma, Gene D Morse

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical pharmacology in drug development, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Cindy J BednaszAIDS Clinical Trials Group Pharmacology Specialty Laboratory, New York State Center of Excellence in Bioinformatics and Life Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA.
Charles S VenutoAIDS Clinical Trials Group Pharmacology Specialty Laboratory, New York State Center of Excellence in Bioinformatics and Life Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA.
Qing MaAIDS Clinical Trials Group Pharmacology Specialty Laboratory, New York State Center of Excellence in Bioinformatics and Life Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA.
Gene D MorseAIDS Clinical Trials Group Pharmacology Specialty Laboratory, New York State Center of Excellence in Bioinformatics and Life Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA.
AIDS Clinical Trials Group · US

Funding

Leadership and Operations Center (LOC), AIDS Clinical Trials Group (ACTG); LOC 1/UM1AI068636 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Joseph J Eron, RAJESH T GANDHI · 2011 to 2026
$1073.1M
Validation, CLIA and Qualification (VQC): Enhancing the RS ratio as a tool for AIDS Clinical Trial Group (ACTG) tuberculosis trialsUM1AI106701 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Grace M Aldrovandi · 2014 to 2026
$116.8M
HIV Research Training ProgramD43TW010313 · FIC · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI Charles Enos Chiedza Maponga, Gene D. Morse · 2016 to 2026
$3.2M
Quantitative Pharmacology for Accelerating Drug Development for HIV/HCV Co-Infected PatientsK23AI108355 · NIAID · UNIVERSITY OF ROCHESTER · PI VENUTO, CHARLES STANLEY · 2015 to 2019
$720k
Antiretroviral pharmacogenomics, pharmacokinetics and toxicity in neuroAIDSK08MH098794 · NIMH · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MA, QING · 2012 to 2016
$599k
FIC NIH HHS D43 TW010313NIAID NIH HHS HHSN272201500006CNIAID NIH HHS K23 AI108355NIAID NIH HHS UM1 AI068636NIAID NIH HHS UM1 AI106701NIMH NIH HHS K08 MH098794
6 · The paper itself

Abstract

There are many factors that can affect the pharmacokinetics (PK) of drugs. Pathophysiological changes from disease states can alter the mechanisms that control the PK of antiretrovirals (ARVs), direct-acting antivirals (DAAs), and addiction treatment medications. Drug-drug interaction pathways of certain ARVs and DAAs can be very complex, with agents being substrates, inhibitors, or inducers of multiple metabolic and transporter pathways. Buprenorphine and methadone may be used in HIV- and hepatitis C virus (HCV)-infected patients and may also be affected by drug interactions. Current research is focused on novel PK analyses, which aim to describe the PK of agents within organs that host the infection of interest, such as within hepatocytes during treatment for HCV. Modeling techniques allow for the prediction of drug PK in specific organs and the plasma compartment. This review will provide a summary of these areas while exploring PK considerations for ARVs, DAAs, and addiction treatment medications.

Indexed as

Anti-Retroviral AgentsDrug InteractionsDrug Therapy, CombinationHepatitis CHumansLiverSubstance-Related DisordersAnti-Retroviral Agentsantiretroviraldirect-acting antiviraldrug-druginteractionpharmacokineticpharmacokinetic modeling

Identifiers

PMID28263465
PMCPMC5341144
OpenAlexW2594868282

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.